InsightaaS: Forrester Research is one of the world’s leading IT analyst firms — it is generally thought to be a key source of insight into and influence over use of new technologies. The company's blog page acts as a "roll-up" of blogs by its analysts. Today, we excerpt a post by data visualization specialist Ryan Morrill, in which he looks at how data visualization is used by data scientists and more mainstream users.
When you’re creating content – whether it’s a film, a sales presentation, or an article on maximizing your Thanksgiving leftovers – it’s always important to consider who your audience is; this also holds true for data visualization. I’ve touched upon this in my previous blog posts, but let‘s take a closer look at the audience spectrum specific to data visualization.
Imagine a spectrum: On one end, let’s say the extreme left, we have the analysts – the scientists – starved of data and wanting as much of it as possible. In fact, there is too much data, and they need an easier way to scan it all to help illustrate relationships and patterns. This is where data visualization can help. The data is raw, and they are digging through it to discover their own conclusions, so a visualization that enables this exploration of the data is crucial. There are usually several dimensions squeezed into a small amount of space, so it’s important to balance the graphic – keeping it both compact and clean. Maps are one example – from heatmaps showing cancer rates across US districts to subway maps; interactive dashboards are another – from Google Finance to the range of examples that tableau presents. They don’t start out with any specific storyline, and the viewer has full control in navigating all the information.
On the other end of the spectrum, we have an audience who is not savvy with the data...